The secondary transmission in a television (hereinafter: TV) spectrum relies on interference control. Secondary users (hereinafter: SU) of the spectrum are not allowed to cause interference to the primary system beyond acceptable limits. A secondary user refers to a White Space Device (hereinafter: WSD). A system that comprises several WSD:s is called a secondary system.
The aggregate interference can be computed by summing the interfering power from each individual transmitter. Such summation assumes that we know the position of each transmitter. The Federal Communications Commission (hereinafter: FCC) has decided that the spectrum access on the TV whitespaces is to be based on geolocation database that stores the location of the secondary users. Also the Great Britain Office of Communications (hereinafter: OFCOM) is currently planning geolocation databases. The databases are likely to store the location information of the secondary system base stations. However, it may be problematic to provide accurate location of the secondary users.
Although the WSD:s can be equipped with Global Positioning System (hereinafter: GPS) receivers to localize themselves, the position information might not be available in indoor scenarios and dense urban deployments where the high rise buildings can shadow the path between the terminals and satellites. Also the task of computing the aggregate interference based on the exact position of all the secondary users is likely to be computationally demanding. A new method is needed to compute at one time the terminal locations change.
Hong et al. have found (in “Interference modeling of cognitive radio networks”, X. Hong, C-X Wang, and J. Tompson, in IEEE VTC 2008-spring, pp. 1851-1855, 2010, XP031255885, ISBN: 978-1-4244-1644-8) that the position information can be disregarded if the transmitters' location are modelled as a random Poisson point process.
Yi Shi, Y. Thomas Hou, Huabei Zhou and Scott F. Midkiff have in their article “Distributed Cross-Layer Optimization for Cognitive Radio Networks”, published in IEEE Transactions on Vehicular Technology, IEEE Service Center, Piscataway, N.J., US, vol. 59, no-8, pages 4058-4069, XP011349028, ISSN: 0018-9545, DOI: 10.11109/TVT.2010.2058875, disclosed the use of the protocol interference model. In this model, the footprint of the transmitter is described as the area where the transmitter generates interference.
The randomly located transmitter is characterized by its transmission power distribution. The aggregate interference is computed as a convolution of distributions. Unfortunately, if the user is located in an arbitrarily shaped area we have to compute the power distribution numerically.
An alternative approach is to compute the aggregate interference as an integral over the spatial power density emitted from the secondary deployment area as suggested by Hoven and Sahai (in “Power scaling for cognitive radio,”, N. Hoven, A. Sahai, in International Conference on Wireless Networks, Communications and Mobile Computing, vol. 1, pp. 250-255, 2005) and Shankar and Cordeiro (in “Analysis of aggregated interference at DTV receivers in TV band,”, S. Shankar, C. Cordeiro, in CrownCom 2008, IEEE, Singapore, pp. 1-6).
Unfortunately, the model proposed by Hoven and Sahai does not contain fading and it is evaluated only for infinite area. The method of Shankar and Cordeiro considers location of all transmitters. Consequently, the model proposed by Shankar and Cordeiro becomes computationally demanding if applied on a large secondary system coverage area.
Straight-forward application of the geolocation database approach or stochastic geometric approach leads to a centralized design in which one central administration will need to have access to full information and then compute the aggregate interference. If multiple entities are allowed to control the access to spectrum, then they must share full information on the secondary user powers and locations.
The use of geolocation databases with sharing of full information about the secondary user powers and locations is not only computationally challenging and difficult to administer but also likely to jeopardize the privacy of the secondary users since the location of a user may be deduced from the location of the terminal he or she is currently using. In addition, the handling of private information may be unacceptable in view of current or planned privacy legislation situation in some countries.